Contactless Measurement of Respiratory Rate Using UWB Radar

Abstract

his master thesis investigates the possibility of remotely measuring respiratory rate during daily life physical non-stationary activity using an IR UWB radar system. The radar signals were processed using Independent Component Analysis (ICA) and Empirical Wavelet Transform (EWT) methods to extract respiratory rate information. The aim was to determine whether the combination of the IR UWB radar system and signal processing techniques can provide an accurate estimate of respiratory rate wirelessly. The outcome of this study suggests that the proposed approach has potential for effective and non-contact monitoring of respiratory rate. The algorithm was evaluated against respiratory rate data obtained through a resistance chest belt during the experiments, and achieved a p-value of the Pearson correlation coefficient analysis of 0.94 and a mean error (ME) value of -0.41, as indicated by the results of the Bland-Altman plot.